Empirical evaluation of five algorithms for the initialization phase of the k-Means algorithm

Author:

do Carmo Nicoletti Maria12,de Oliveira Anderson Francisco1

Affiliation:

1. Centro Universitário C. Limpo Paulista, C. L. Paulista, SP, Brazil

2. Universidade Federal de S. Carlos, S. Carlos, SP, Brazil

Publisher

IOS Press

Reference41 articles.

1. A survey of clustering algorithms for big data: taxonomy and empirical analysis;Fahad;IEEE Transactions on Emerging Topics in Computing,2014

2. A.F. Oliveira and M.C. Nicoletti, (2018) Favouring the k-means algorithm with initialization methods, In: Abraham A, Cherukuri A, Melin P, Gandhi N. (eds), Intelligent Systems Design and Applications. ISDA 2018 2018. Advances in Intelligent Systems and Computing, v. 940, Springer, Cham.

3. A.F. Oliveira, Favouring the performance of k-Means via centroid initialization methods, M. Sc.dissertation, UNIFACCAMP, C.L. Paulista, Brazil, 2018 (in Portuguese).

4. Clustering aggregation;Gionis;ACM Transactions on Knowledge. Discovery. Data (ACM TKDD),2007

5. Data clustering: 50 years beyond K-means;Jain;Pattern Recognition Letters,2010

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1. Semantic process mining: A conceptual application of main tools, framework and model analysis;International Journal of Hybrid Intelligent Systems;2020-09-28

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